Cyclomatic Complexity

Cyclomatic complexity is a metric developed by Thomas McCabe in 1976 to quantify the complexity of a program's control flow.

How It Works

It is calculated by analyzing the control flow graph of a function or method. The nodes represent code blocks, and the edges represent control paths (e.g., if, while, for, case, etc.).

The formula is: M = E - N + 2P

• M = Cyclomatic complexity
• E = Number of edges
• N = Number of nodes
• P = Number of connected components (typically 1 for a single function)

What it describes

• M = 1: Straight-line code (no conditionals or branches)
• M between 2–10: Simple, manageable code
• M > 10: Complex, potentially harder to test and maintain
• M > 20: Very complex and likely needs refactoring

Why It Matters

High cyclomatic complexity can:

• Increase the risk of bugs
• Make unit testing more difficult
• Indicate that the function is doing too much

Best Practices

• Break down functions with high complexity into smaller ones
• Use guard clauses to reduce nesting
• Aim to keep complexity below 10 where possible

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Possible paths

These are the possible paths for the following code snippet:

• P,1,2,3,K
• P,1,2,5,6,2,3,K
• P,1,2,5,7,8,2,3,K
• P,1,2,5,7,9,2,3,K
• P,1,2,5,7,9,10,2,3,K

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